code: def _load_builder_from_code(
      name: str,
  ) -> BuilderToDocument:
      """Load the builder, config,... to document."""
      builder_cls = tfds.builder_cls(name)
      sections = _get_sections(builder_cls)
  
      if builder_cls.BUILDER_CONFIGS:  # Builder with configs
  
          def get_config_builder(config) -> tfds.core.DatasetBuilder:
              return tfds.builder(builder_cls.name, config=config)
  
          with futures.ThreadPoolExecutor(
              max_workers=_WORKER_COUNT_CONFIGS
          ) as tpool:
              config_builders = list(
                  tpool.map(
                      get_config_builder, builder_cls.BUILDER_CONFIGS
                  ),
              )
          return BuilderToDocument(
              sections=sections,
              namespace=None,
              builder=config_builders[0],
              config_builders=config_builders,
          )
      else:  # Builder without configs
          return BuilderToDocument(
              sections=sections,
              namespace=None,
              builder=builder_cls(),  # pytype: disable=not-instantiable
              config_builders=[],
          )
  
imports: from concurrent import futures
  import dataclasses
  import functools
  from typing import Any, Iterator, List, Optional, Set, Type
  from absl import logging
  import tensorflow_datasets
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.scripts.documentation import collection_markdown_builder
  from tensorflow_datasets.scripts.documentation import dataset_markdown_builder
  from tensorflow_datasets.scripts.documentation import doc_utils
  import tqdm
label_desc: Use image node_id 6 for calling a global function with example usage: _load_builder_from_code(name) and returns: BuilderToDocument, BuilderToDocument, tfds